The concept behind human fingerprint identification and analysis is to examine the characteristics of a fingerprint in order to identify its unique attributes. In translating the physical print into unique recognition data by an analysis tool 100 (e.g., high resolution imaging device) which may be subsequently stored, various data points called minutiae are gathered, such as depicted in FIG. 2. Traditionally, uniqueness of a physical fingerprint was identified via the magnification of an image of the print 102 and visual analysis of characteristics of the magnified print. Minutiae is essentially data representative of elements of interest. When one considers that no two fingerprints are identical, it is thus so that no sets of fingerprint minutiae points are alike. Minutiae may be compiled in various ways, such as two-dimensional coordinates representative of specific elements of interest 106, as a function of the relative distances between select elements of interest, as a function of relative angular measurements between select elements of interest, etc. Such information, in compilation, may be associated with a unique identification tag 108 as being representative of a sole individual. Hence, the statistical probability of duplicate fingerprints, and therefore duplicate sets minutiae data, is so astronomically high as to be considered virtually impossible—even for identical twins.
The number and location elements of interest for compiling the minutiae vary from finger to finger and from person to person for any particular finger (for example, a person's left thumb versus their right). When a set of fingerprint images is obtained from an individual, the data number for a minutiae is recorded for each finger. The precise locations of the minutiae are also recorded in the form of numerical coordinates for each finger. Other minutiae data may also be collected and associated with the fingerprint image, such as scar tissue data or the like for distinct identification purposes. The result is the generation of a function based on the compilation of this minutiae data that can be entered and stored in a computer database. Having acquired this data, a computer can rapidly compare this functional data against any previously stored fingerprint data in order to potentially link to an original source.
Unlike fingerprint analysis, where inherently unique aspects of a physical fingerprint 100 are relied upon, most document identification methods involve the decoding of, or recognition of physical content or markings on the document as identification means. For example, in the mail processing industry, where postal authority rules and regulations must be adhered to in order to avoid mail fraud and enable postage discounts for mailers, document identification and recognition is critical. Usually, a postal authority, relies solely on a sequence number, barcode, postal ZIP Code or other physical marking selectively placed upon the mail article as a means of identifying it from other articles in a batch of mail and/or from among all mailpieces. Likewise, in many manufacturing or goods distribution industries where unique documentation (e.g., labels) is required to distinguish a particular good or manufacture, unique scancodes, item numbers or serial numbers are used. Even in the field of document forensics, which may involve the determination of signature forgery, mark authentication, writing indentations, smudge mark analysis, etc., there still is a dependency upon analysis of the content (characters and/or objects) i.e., object character recognition of that which is printed or written on the document.
Suffice to say, there is currently no system or method for enabling the complete identification of a document, especially throughout its lifecycle, based on the same principles that enable a fingerprint to be distinctly identified from all others. Because it is common for documents to be printed and/or copied such that they possess identical physical content or markings (e.g., charts, words, logos, letter head, etc.), there is a need in the art for a system and method for unique document identification and analysis enablement would require the generation of minutiae data that is not limited to or based solely upon such content or markings, such as a barcode or the like. Conventional techniques of adding unique identifiers to a document for later identification involves added expense. Furthermore, the there is a need in the art for a system that enables a client to easily gain access to relevant data pertaining to a document throughout its life cycle, on demand.